1. Field of the Invention
The present invention relates in general to methods for extracting and recognizing a pattern in an image, and relates in particular to a method for extracting a particular pattern with an image, and identifying a pattern and its location concurrently, to enable automatic recognition of characters on a license plate for example, and relates also to a method for judging an abnormality in an image.
This application is based on patent application Nos. Hei 9-212104 and Hei 10-71094 filed in Japan, the contents of which are incorporated herein by reference.
2. Description of the Related Art
Methods for extracting certain features of an image, such as particular patterns formed by characters, from an image view (shortened to image hereinbelow) using information processing apparatus are reported in "Extraction of letters from shaded image", Journal of Information Processing Society, CV Seminar (Reference A) for example.
Also, conventional pattern recognition methods, especially recognition of license plates, have been performed by a process of preliminary binary conversion of the image, followed by pattern matching. This method is successful if the image is clear and has sufficient resolution, then the characters can be independently binarized so that the results can be analyzed. However, recognition is sometimes difficult or impossible when the image has insufficient resolution or the object is unclear or the images are partially touching, shielded or smeared.
Other methods for pattern matching without binarization are based on correlation factor. This method is able to manage partial image touching and shielding problems, but it is inadequate for dealing with identification problems caused by illumination.
Regarding emergency detection techniques, monitoring cameras are often based on image abnormality detection derived from the above-noted pattern extraction and recognition technologies, therefore, any change in an image can constitute a criterion for abnormality. Judgment that an image contains a change is generally arrived at by computing the difference between a current image and the reference image which would normally be viewed by the camera.
However, although methods which are not adversely affected by shadows are known, as reported in reference A, existing methodologies suffer from a common problem that accurate pattern extraction cannot be carried out in many cases, including the cases when there are noise or shadows in an image or when the pattern to be extracted is locally shielded or when the object is not a character.
With respect to currently available image abnormality detection technologies, when there is obstructive element in the image, shadow of a building for example, these methods will recognize the shadow as an image abnormality thereby generating excessive false warnings.
Also, the extent of abnormality is an important criterion for noting an emergency. However, if a genuine image abnormality exists but it is affected by pseudo effects of building shadow and others, apparent abnormality region in an image and the actual abnormality region do not match and accurate area of the actual image abnormality cannot be established, and the process is unable to reach a correct conclusion.